I've built a physics-based neural engine achieving: - Conservation: 5.27×10^-13 (machine precision) - Drift: 10^-17 (essentially zero) - Bit-exact reproducible

I've built a physics-based neural engine achieving: - Conservation: 5.27×10^-13 (machine precision) - Drift: 10^-17 (essentially zero) - Bit-exact reproducible replay - Live topology switching (chain→strong→ring→grid) - 336.6 samples/s on CPU This enables century-scale simulations without drift accumulation. No CUDA. No tensor cores. Pure deterministic compute. Implications: - Backtesting without numerical artifacts - Climate models that don't diverge - Provable AI behavior for regulatory compliance